Presence Of Different Sources Research Articles

A robust quality estimation method for medical image segmentation with small datasets

The quality check of automatic image analysis results is a necessity to eliminate poor outcomes. There are few work on segmentation quality estimation when there is no reference mask available. Generative-based and regression approaches generally have strict assumptions on shape/contrast of anatomical structures, which may fail when there are abnormalities in images or in the presence of domain shift. Ensemble approach promises more generalisability to various types of images; however, they are costly to train. Also, none of these methods were designed for small datasets. To address these shortcomings, this paper presents a segmentation quality estimation method for small datasets with arbitrary dimensions, which is validated with 2D, 3D and 4D image datasets with roughly 20 training images, and on the segmentation of retinal vessel and left atrium segmentation. Although our method uses an ensemble for image segmentation, its design reduces its parameter size. We describe possible scenarios relating the amount of agreement across the base models’ outputs in an ensemble to quality scores; then, present a technique to deal with high quality score estimation for poor segmentation as a result of the base models to largely agree on mistakes. We assess the performance of our method in the presence of different sources of domain shift, and compare it with methods selected from the aforementioned approaches. We found robust quality score estimation, generalisable to different datasets. Our code would be available upon acceptance.

European Green Deal: Satellite Monitoring in the Implementation of the Concept of Agricultural Development in an Urbanized Environment

To improve energy and environmental security in urban environments and in accordance with the requirements of the EU, the task of sustainable developing agriculture in urban agglomerations and monitoring it using satellite images becomes relevant. The aim of the work is the development of methods and means for determining stable islands of thermal energy to substantiate the optimal locations for plant growing practices in the metropolis. The research was conducted in Kyiv, the largest metropolis of Ukraine. Data from the Landsat 8 and 9 satellites were used because of the free data and they have better spatial resolution and an available archive of observation results. It was established that the temperature map of the city of Kyiv shows differences in temperature between different parts of the city, probably due to the presence of different sources of heat radiation. It is obvious that the standard deviation of the temperature in the plots depends on many factors, in particular, the season and the type of land use. It is necessary to find alternative solutions for the development of crop production in this area, taking into account the characteristics of thermal emissions. Based on software products from free satellite monitoring providers, EO Browser, a specialized software solution (web application) has been created for monitoring agricultural plantations in an urban environment. A collection of LANDSAT 8 satellite images was used. Areas with stable heat emissions were found, which are due to the operation of a modern shopping and entertainment center, and non-traditional crops for landscaping adapted to its design are proposed. As a result of research, strong heat emissions were recorded for some objects, for them the temperature exceeds the surrounding area by 4 °C, while the minimum standard deviation in January is 0.5 °C, the maximum in July is 2.8 °C, in April and October—1.7 °C and 1.2 °C, respectively.

Effect of Different Sources of Nutrients on Growth, Yield and Quality of Mung Bean (Vigna radiata L.)

A pot experiment was conducted in the experimental research farm of Department of Soil Science, SAS, Nagaland University, and Medziphema campus, Nagaland in the period of June to September 2022 to make a study on “Effect of different sources of nutrients on growth, yield and quality of mung bean (Vigna radiata L.). The experiment was laid out in Complete Randomized Design (CRD) with 12 treatments and 3 replications. The study revealed that the incorporation of different sources of nutrients significantly influenced that the plant growth, yield attributes and quality parameters i.e., NPK and protein content, Nutrient uptake, and availability of nutrients in soil after harvest of green gram. The crop growth attributes such as plant height, number of leaves plant-1 and number of branches plant-1 were significantly influenced by its application. The highest seed yield of 11.67 g pot-1and stover yield of 37.88 g pot-1 recorded with the treatment of 100% RDF+PSB+FYM was significantly superior over all treatments. The quality of green gram was improved by 100% RDF+PSB+FYM in the presence of different sources of nutrients. The highest nutrient content and highest nutrient uptake by green gram was also recorded highest with the treatment 100% RDF+PSB+FYM. The available nutrients (NPK), cation exchange capacity, organic carbon, soil respiration, microbial biomass carbon in soil was also found to be more due to the treatment of 100% RDF+PSB+FYM.

RADIOCARBON DATING OF STRAW FRAGMENTS IN THE PLASTERS OF ST. PHILIP CHURCH IN ARCHAEOLOGICAL SITE HIERAPOLIS OF PHRYGIA (DENIZLI, TURKEY)

ABSTRACTAbsolute dating of plasters and mortars clearly represents a key information to study important structures and buildings that may have undergone a difficult story starting from their construction. This is for instance the case of the architectures in the archaeological site of Hierapolis (Denizli, Turkey). However, when discussing about the possibility to apply radiocarbon (14C) dating, in this site the presence of different sources of contaminants, due to the geological and geochemical conditions and to the used raw materials, prevents the binder dating. As an alternative, we thus decided to focus on the small fragments of straw that had been used as additives in the mortar/plaster matrices. The fragments were identified, selected and dated using a 14C experimental set-up specifically optimized for microgram-sized samples. The obtained results were satisfying, even though the measured 14C ages also pointed out some possible criticalities in dating such small samples collected from a carbonaceous matrix.

Seasonal Variation of Aerosol Composition and Sources of Water-Soluble Organic Carbon in an Eastern City of China

The mitigation of aerosol pollution is a great challenge in many cities in China, due to the complex sources and formation mechanism of particulate matter (PM) in different seasons. To understand the particular features of pollution in China and formulate different targeted policies, aerosol samples of PM2.5 were collected from January to October of 2018 in Longyou. The temporal profile of the meteorological parameters and the concentrations of water-soluble inorganic ions (WSIs) and organic matter (OM) were characterized. An Aerodyne High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-TOF-AMS) was also applied to further analyze the composition of water-soluble organic carbon (WSOC). The sources of WSOC were resolved by positive matrix factorization (PMF) analysis. The origin of air parcels and potential sources of WSOC were analyzed using a backward trajectory and potential source contribution function (PSCF). Winds from the northeast dominated each sampling period, and the relative humidity did not show a significant difference. The results showed that the proportion of OM in PM2.5 was the highest in summer and decreased in spring, autumn, and winter in turn. Four organic aerosol (OA) factors, including a hydrocarbon-like factor, a coal combustion factor, and two oxygenated OA factors, were identified in the WSOC by means of PMF analysis. The hydrocarbon-like OA (HOA) contributed the majority of the WSOC in summer, while the contribution of the coal-combustion OA (CCOA) increased significantly in winter, suggesting the presence of different sources of WSOC in different seasons. The air parcels from the north of China and Zhejiang province contributed to the CCOA in winter, while those from the marine regions in the south and southeast of China mainly contributed to the HOA during spring and summer. The weighted PSCF (WPSCF) analysis showed that the regions of east Zhejiang province were the main contributors, which means that local and regional emissions were the most probable source areas of WSOC. It implied that not only were the emissions control of both local and regional emissions important but also that the transport of pollutants needed to be sufficiently well accounted for to ensure the successful implementation of air pollution mitigation in Longyou.

Online estimation of unknown aerodynamic forces acting on AWE systems

• An EKF can be used for estimating online unknown aerodynamics forces that act on AWE systems. • The control performance of AWE systems can be improved by considering the estimated aerodynamic forces. • By using the EKF, less sensors are necessary to implement nonlinear control laws. • The EKF use increases the robustness of the AWE system in the presence of different sources of uncertainties. • The EKF allows for getting reliable estimations of the aerodynamic coefficients. Airborne Wind Energy systems (AWE) represent a promising solution to environmental challenges that has revolutionized research in the wind industry. The studied AWE system in this work is equipped with a multicopter drone in order to perform take-off and landing maneuvers and the objective consists in presenting an estimation strategy based on an Extended Kalman Filter (EKF) to obtain accurate estimation of the aerodynamic forces needed to improve the performance of the proposed control law for the considered prototype in this study. The proposed method is implemented and tested in a numerical and experimental environment. The obtained results show the effectiveness of the introduced method at estimating unknown forces that act on the system despite the presence of several sources of uncertainty: neglected nonlinearities, poorly known parameters, physical constraints, etc. Moreover, we show that the knowledge of these forces allows one to improve the robustness of the studied AWE system during its take-off and landing phases.

Assessment of contamination levels of heavy metals in the agricultural soils using ICP-OES

ABSTRACT This work was carried out to monitor contamination levels of twelve heavy metals (HMs) in the agricultural soils of Kafr El-Zayat city in Egypt. The concentrations of Mg, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Sr, and Pb were determined using inductively coupled plasma optical emission spectroscopy (ICP-OES). Contamination levels were estimated based on various geochemical parameters such as contamination factor (CF), enrichment factor (EF), geo-accumulation index (Igeo), degree of contamination (Cd ), and pollution load index (PLI). The results showed that the majority of investigated soil samples were moderately contaminated (1 ≤ CF < 3) with V, Cr, Co, Cu, Zn, and Sr and had low contamination levels (CF <1) with Mg, Mn, Fe, Ni, and Pb. All investigated elements had geo-accumulation indices smaller than zero indicating uncontaminated soil samples except for V which showed (0 < Igeo < 1) indicating uncontaminated to moderate pollution levels. All soil samples were found to have deficient to minimal enrichment for all investigated HMs based on the average values of EF (EF < 2). Cluster analysis (CA) and principal component analysis (PCA) revealed that HMs were clustered into three groups compromising As and V; Ni, Cr, Mn, Co, Fe, and Mn; and Pb, Cu, Sr, and Zn, which suggests the presence of different sources of pollution. The contribution of anthropogenic sources to V, Cr, Co, Cu, Zn, As, and Sr was estimated to be 45, 30, 26, 11, 23, 27, and 13% of the total metal content, respectively. In general, the investigated agricultural soil samples could be classified as moderately contaminated and polluted based on the Cd factor (Cd = 13.7), and the PLI (PLI = 1.1), respectively.

Antimicrobial Resistance Profiles and Genetic Typing of Salmonella Serovars from Chicken Embryos in China.

Salmonella continues to be a major food and public health burden worldwide that can threaten human health via eating contaminated meats, particularly those originating from chicken. In this study, the antimicrobial resistance profiles, epidemiological characteristics of resistance genes, and pulsed field gel electrophoresis (PFGE-XbaI) typing of 120 non-Pullorum/Gallinarum Salmonella isolates recovered from chicken embryos in Henan province were determined. The antimicrobial resistant phenotypes and evaluation of the extended-spectrum beta-lactamases (ESBLs) producing strains of Salmonella were investigated by the Kirby–Bauer test and the double-disk synergy test. Additionally, 37 antimicrobial resistance genes encoding resistance to five different categories, including aminoglycosides, cephalosporins, sulphonamides, tetracyclines, and β-lactams, were examined by conventional PCR. However, genotyping analysis was conducted by macro-restriction using enzyme XbaI followed by the separation of the restricted DNA fragments by PFGE. The results of this study showed that the studied Salmonella strains were highly resistant to ampicillin (66.67%) and sulfisoxazole (66.67%), while they were all susceptible to meropenem, imipenem, colistin, and chloramphenicol. Additionally, 67.5% (81/120) of the studied strains were multidrug resistant, and 21.67% (26/120) were phenotypically confirmed as ESBLs positive. The statistical analysis showed that resistance depends on the serovars, and ESBLs positive strains showed more multi-resistance than ESBLs negative strains (p < 0.05). The genotypic antimicrobial resistance showed the detection of 14 among the 37 tested genes, and the concordance between genotypic and phenotypic antimicrobial resistance ranged from 0% to 100% depending on the serovars. However, the PFGE-XbaI typing results showed that the examined Salmonella strains were divided into 22 individual subtypes and were grouped in nine clusters, with similarity values ranging from 64.7% to 100%. From this study, we can conclude that the antimicrobial resistance of Salmonella serovars isolated from chicken embryos in Henan province was alarming, with rigorous multidrug resistance, which requires the urgent mitigation of the use of antimicrobial drugs in chicken hatcheries. Additionally, our results showed evidence of the presence of different PFGE patterns among the studied Salmonella serovars, suggesting the presence of different sources of contamination.

Do oil prices and exchange rates affect the US stock market? New evidence from the asymmetric cointegration approach

In this paper, we study the dynamics between US stock prices, exchange rates and oil prices. The data used are quarterly, covers the period from 1986 to 2016 and includes the Standard & Poor's 500 spot prices, the West Texas Intermediate spot prices and the effective exchange rate of US Dollar. We examine the presence of different sources of nonlinearities. The empirical analysis is based on the asymmetric ARDL cointegration methodology proposed by Shin et al (2011). The evidence implies that ignoring possible non-linearities lead to misleading results. The analysis reveals new evidence such as the existence of several structural brakes and asymmetries in both long-run and short-run relationships among the examined variables and that could be of major importance for researchers and other market participants.

Synchronizing Two Superconducting Qubits through a Dissipating Resonator.

A system consisting of two qubits and a resonator is considered in the presence of different sources of noise, bringing to light the possibility of making the two qubits evolve in a synchronized way. A direct qubit–qubit interaction turns out to be a crucial ingredient, as well as the dissipation processes involving the resonator. The detrimental role of the local dephasing of the qubits is also taken into account.

An Italian Multicentre Study Using Different Digital PCR Instruments on BCR-ABL1 Positive Patients at Different Levels of CML Disease

Background: Monitoring of BCR-ABL1 levels by quantitative PCR (qPCR) is essential for the management of CML patients treated with TKIs. Because of intrinsic limits, qPCR does not appear to be an optimal tool to quantify transcript levels around 10% and very low levels of disease. Digital PCR (dPCR), thanks to its intrinsic features, is expected to be more accurate than qPCR in the assessment of molecular MRD as demonstrated in different studies (Huang et al 2015, Franke et al, 2015). In order to hypothesize the use of this new technology in the clinical practice, a standardization process is mandatory.Aim: We started a multicentric study in order to evaluate if different digital PCR instruments and methods can provide aligned results. For this purpose we analyzed the intra-assay reproducibility for each laboratory by calculating the % of coefficient variation (CV%).Methods: Four laboratories were involved in the project: 3 have used a Bio-Rad instrumentation based on a droplet system (1 labs QX200, 2 lab QX100) and 1 used a chip-based instrumentation from Life Technologies (QuantStudio 3D). The assays used were: DigiDrop P210 MasterMix from Bioclarma s.r.l. (2 laboratories), “custom system” (2 laboratories). Tests were performed on cDNAs centrally prepared by one of the laboratory, over a period of 3 weeks. The same materials have been quantified by RT-QPCR to express the result in I.S. and dispatched to the other laboratories involved in the study. 16 RNA pools were prepared at different levels of disease (3 pools for 10% level, 3 pools for 1% level, 3 pools for 0.1% level, 3 pools for 0.01% level, 3 undetectable pools in MR 5.0, 1 pool of donors). Blind digital PCR analysis were performed and repeated in 3 separate sessions. ddPCR was performed in triplicate for BCR-ABL1 using 200 ng of cDNA for each replicate and in duplicate for ABL1 using 100 ng of cDNA for each replicate; the QuantStudio 3D was performed in duplicate for both genes using 50 ng of cDNA for each replicate of BCR-ABL1 and 25 ng of cDNA for each replicate of ABL1 (to avoid the saturation of the control gene).Results: The analysis was based on the data from the 4 laboratories by evaluating both of absolute copies of BCR-ABL1 and ratio (BCR-ABL1/ABL%). The analysis of intra-assay data for each sample in the three sessions and for each center showed that: the QuantStudio 3D system shows an overestimation of the values in all the levels of disease analyzed; 3 laboratories revealed 15% of positivity in the healthy samples (4/27 replicates); the laboratory with a chip-based approach didn't reveal any positivity but it tested only 50 ng of cDNA for each replicates (versus 200 ng in ddPCR) 2 out of 3 samples considered undetectable MR 5.0 in RT-qPCR resulted positive in 3 out of 4 laboratories. Then, for each sample we investigated how results obtained (ratio% and absolute copies of BCR-ABL1) for each sample were distributed around the median value calculated from all laboratories. Outlier values were excluded from the analysis according to Critical values for Grubbs outlier test. [Grubbs F: Technometrics 1969; 11(1):1-21]. The analysis showed that when expressed in ratio results of 3 out of 4 labs using ddPCR were within the range of ±2SD, the lab using the QuantStudio 3D had several values outside the ±2SD limit; regarding the absolute copies of BCR-ABL1 all values obtained, except for 2, were aligned around the mean value and fall within the range of the ±2SD. (Fig. 1) Finally, CV% calculated on the results (ratio% and absolute copies of BCR-ABL1) produced in 3 sessions of dPCR in each laboratory were similar for each lab for all levels of disease (Tab.1)Conclusion: This multicentric Italian experience has highlighted a good overlapping of final data in terms of accuracy and reproducibility at different levels of disease, despite the presence of different sources of methodological and instrumental variability. Our results may suggest an improvement on variability respect to those obtained in RT-qPCR (Branford S. et al 2006). Despite the presence of different sources of methodological and instrumental variability, there is a good alignment of multicentric results. [Display omitted] DisclosuresFava:Pfizer: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Varotto:Bioclarma s.r.l.: Employment. Barberio:Bioclarma s.r.l.: Equity Ownership. Saglio:BMS: Consultancy, Honoraria; Ariad: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Ariad: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Roche: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Pane:Novartis: Honoraria, Speakers Bureau. Martinelli:PFIZER: Consultancy; ARIAD/INCYTE: Consultancy; AMGEN: Consultancy; ROCHE: Consultancy; JOHNSON & JOHNSON: Consultancy; CELGENE: Consultancy. Specchia:Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Incyte: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria.

Fundamental physics with ESPRESSO: Towards an accurate wavelength calibration for a precision test of the fine-structure constant

Observations of metal absorption systems in the spectra of distant quasars allow one to constrain a possible variation of the fine-structure constant throughout the history of the Universe. Such a test poses utmost demands on the wavelength accuracy and previous studies were limited by systematics in the spectrograph wavelength calibration. A substantial advance in the field is therefore expected from the new ultra-stable high-resolution spectrograph ESPRESSO, which was recently installed at the VLT. In preparation of the fundamental physics related part of the ESPRESSO GTO program, we present a thorough assessment of the ESPRESSO wavelength accuracy and identify possible systematics at each of the different steps involved in the wavelength calibration process. Most importantly, we compare the default wavelength solution, which is based on the combination of Thorium-Argon arc lamp spectra and a Fabry-Pérot interferometer, to the fully independent calibration obtained from a laser frequency comb. We find wavelength-dependent discrepancies of up to 24 m s−1. This substantially exceeds the photon noise and highlights the presence of different sources of systematics, which we characterize in detail as part of this study. Nevertheless, our study demonstrates the outstanding accuracy of ESPRESSO with respect to previously used spectrographs and we show that constraints of a relative change of the fine-structure constant at the 10−6 level can be obtained with ESPRESSO without being limited by wavelength calibration systematics.

Two-Stage Robust Telemedicine Assignment Problem with Uncertain Service Duration and No-Show Behaviours

The current pandemic of COVID-19 has caused significant strain on medical center resources, which are now the main places to provide the rapid response to COVID-19 through the adoption of telemedicine, especially for the health care delivery, in order to meet patients' needs and reduce the transmission of the virus and protect medical practitioners from infection while minimizing their exposure to the public and in-person visits. Thus it is crucial for the healthcare managers to make an effective assignment plan for the patients and telemedical doctors when providing telemedicine services in a highly uncertain environment. In this regard, this paper presents the first comprehensive study of a two-stage robust optimization telemedicine assignment problem when different sources of uncertainty are incorporated in practice, including uncertain service duration, no-show behaviours of both patients and telemedical doctors. To overcome the difficulty of resolution for such a model with a max-min based mixed-integer linear programming recourse problem, from the algorithmic viewpoint we propose an efficient nested column-and-constraint generation (CCG) solution scheme that decomposes the model into the outer level problem and inner level problem, which both can be solved by CCG algorithm. Our computational results show that our method can solve the problems of realistic sizes within a reasonable time (e.g., up to 100 patients, 10 telemedical doctors, and 200 empirical scenarios within one and a half hours). On the empirical side, this paper has also demonstrated how to choose the optimal hyper-parameters to make an optimal trade-off between cost management and the coverage level of the served patients in the presence of different sources of uncertainty, and what's the added value of our robust policy when compared with its two-stage stochastic programming counterpart model.

Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI

Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, most existing approaches are based on deterministic models, neglecting the presence of different sources of uncertainty in such problems. Here we introduce methods to characterise different components of uncertainty, and demonstrate the ideas using diffusion MRI super-resolution. Specifically, we propose to account for intrinsic uncertainty through a heteroscedastic noise model and for parameter uncertainty through approximate Bayesian inference, and integrate the two to quantify predictive uncertainty over the output image. Moreover, we introduce a method to propagate the predictive uncertainty on a multi-channelled image to derived scalar parameters, and separately quantify the effects of intrinsic and parameter uncertainty therein. The methods are evaluated for super-resolution of two different signal representations of diffusion MR images—Diffusion Tensor images and Mean Apparent Propagator MRI—and their derived quantities such as mean diffusivity and fractional anisotropy, on multiple datasets of both healthy and pathological human brains. Results highlight three key potential benefits of modelling uncertainty for improving the safety of DL-based image enhancement systems. Firstly, modelling uncertainty improves the predictive performance even when test data departs from training data (“out-of-distribution” datasets). Secondly, the predictive uncertainty highly correlates with reconstruction errors, and is therefore capable of detecting predictive “failures”. Results on both healthy subjects and patients with brain glioma or multiple sclerosis demonstrate that such an uncertainty measure enables subject-specific and voxel-wise risk assessment of the super-resolved images that can be accounted for in subsequent analysis. Thirdly, we show that the method for decomposing predictive uncertainty into its independent sources provides high-level “explanations” for the model performance by separately quantifying how much uncertainty arises from the inherent difficulty of the task or the limited training examples. The introduced concepts of uncertainty modelling extend naturally to many other imaging modalities and data enhancement applications.

Amelioration of copper toxicity to a tropical freshwater microalga: Effect of natural DOM source and season

Australian tropical freshwaters can experience extreme seasonal variability in rainfall and run off, particularly due to pulse events such as storms and cyclones. This study investigated how seasonal variability in dissolved organic matter (DOM) quality impacted the chronic toxicity of copper to a tropical green alga (Chlorella sp.) in the presence of two concentrations of DOM (low: ∼2 mg C/L; high: ∼10 mg C/L) collected from three tropical waters. Copper speciation and lability were explored using diffusive gradients in thin-films (DGT) and modelled maximum dynamic concentrations (cdynmax) using data derived from the Windermere Humic Aqueous Model (WHAM VII). Relationships between copper lability and copper toxicity were assessed as potential tools for predicting toxicity. Copper toxicity varied significantly with DOM concentration, source and season. Copper toxicity decreased with increasing concentrations of DOM, with 50% growth inhibition effect concentrations (EC50) increasing from 1.9 μg Cu/L in synthetic test waters with no added DOM (0.34 mg C/L) up to 63 μg Cu/L at DOM concentrations of 9.9 mg C/L. Copper toxicity varied by up to 2-fold between the three DOM sources and EC50 values were generally lower in the presence of wet season DOM compared to dry season DOM. Linear relationships between DGT-labile copper and dissolved copper were significantly different between DOM source, but not concentration or season. Modelled cdynmax consistently under-predicted labile copper in high DOM treatments compared to DGT measurements but performed better in low DOM treatments, indicating that this method is DOM-concentration dependent. Neither speciation method was a good surrogate for copper toxicity in the presence of different sources of natural DOM. Our findings show that DOM source and season, not just DOM concentration, affect copper toxicity to freshwater biota. Therefore, DOM quality should be considered as a toxicity-modifying factor for future derivation of bioavailability-based site-specific water quality guideline values.

Construct Validity of an Instrument for Assessment of Reflective Writing-Based Portfolios of Medical Students.

PurposeAssessment of reflective writing for medical students is challenging, and there is lack of an available instrument with good psychometric properties. The authors developed a new instrument for assessment of reflective writing-based portfolios and examined the construct validity of this instrument.MethodsAfter an extensive literature review and pilot testing of the instrument, two raters assessed the reflective writing-based portfolios from years 2 and 3 medical students (n=135) on three occasions. The instrument consists of three criteria: organization, description of an experience and reflection on the experience. We calculated the reliability of scores using generalizability theory with a fully crossed design and two facets (raters and occasions). In addition, we measured criterion validity by testing correlations with students’ scores using other assessment methods.ResultsThe dependability (Φ) coefficient of the portfolio scores was 0.75 using two raters on three occasions. Students’ portfolio scores represented 46.6% of the total variance across all score comparisons. The variance due to occasions was negligible, while the student–occasion interaction was small. The variance due to student–rater interaction represented 17.7%, and the remaining 27.7% of the variance was due to unexplained sources of error. The decision (D) study suggested that an acceptable dependability (Φ = 0.70 and 0.72) can be achieved by using two raters for one and two occasions, respectively. Finally, we found moderate to large effect-size correlations between students’ scores in reflective writing-based portfolios and communication skills (r = 0.47) and PBL tutorials (r = 0.50).ConclusionWe demonstrated the presence of different sources of evidence that support construct validity of the study instrument. Further studies are warranted before utilizing this instrument for summative assessment of students’ reflective writing-based portfolios in other medical schools.

Application of land use regression to assess exposure and identify potential sources in PM2.5, BC, NO2 concentrations

BackgroundUnderstanding spatial variation of air pollution is critical for public health assessments. Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations. However, they have limited application in China due to the lack of spatially resolved data. ObjectiveBased on purpose-designed monitoring networks, this study developed LUR models to predict fine particulate matter (PM2.5), black carbon (BC) and nitrogen dioxide (NO2) exposure and to identify their potential outdoor-origin sources within an urban/rural region, using Taizhou, China as a case study. MethodTwo one-week integrated samples were collected at 30 PM2.5 (BC) sites and 45 NO2 sites in each two distinct seasons. Samples of 1/3 of the sites were collected simultaneously. Annual adjusted average was calculated and regressed against pre-selected GIS-derived predictor variables in a multivariate regression model. ResultsLUR explained 65% of the spatial variability in PM2.5, 78% in BC and 73% in NO2. Mean (±Standard Deviation) of predicted PM2.5, BC and NO2 exposure levels were 48.3 (±6.3) μg/m3, 7.5 (±1.4) μg/m3 and 27.3 (±8.2) μg/m3, respectively. Weak spatial corrections (Pearson r = 0.05–0.25) among three pollutants were observed, indicating the presence of different sources. Regression results showed that PM2.5, BC and NO2 levels were positively associated with traffic variables. The former two also increased with farm land use; and higher NO2 levels were associated with larger industrial land use. The three pollutants were correlated with sources at a scale of ≤5 km and even smaller scales (100–700m) were found for BC and NO2. ConclusionWe concluded that based on a purpose-designed monitoring network, LUR model can be applied to predict PM2.5, NO2 and BC concentrations in urban/rural settings of China. Our findings highlighted important contributors to within-city heterogeneity in outdoor-generated exposure, and indicated traffic, industry and agriculture may significantly contribute to PM2.5, NO2 and BC concentrations.

Adsorption, aggregation and sedimentation of titanium dioxide nanoparticles and nanotubes in the presence of different sources of humic acids.

Environmental behavior, bioavailability and risks posed by TiO2, nanomaterials (TiO2 NMs) in surface waters are affected by morphologies of the particles and geochemistry, including pH, inorganic and organic matter. Here, the adsorption, aggregation and sedimentation of TiO2 nanoparticles (TiO2 NPs) and nanotubes (TiO2 NTs) were investigated in the presence of Elliott Soil humic acid (HAE) and Suwannee River humic acids (HAS). The adsorption amount of HA on TiO2 NMs was inversely proportional to pH of solution. Maximum adsorption amount of HA on the surface of TiO2 NMs follows the order TiO2 NPs + HAE (236.05 mg/g) > TiO2 NTs + HAE (146.05 mg/g) > TiO2 NTs + HAS (70.66 mg/g) > TiO2 NPs + HAS (37.48 mg/g). Stability of TiO2 NPs and TiO2 NTs largely depended on their isoelectric point, morphology and solution pH in the absence of HA. Dispersion of TiO2 NMs was enhanced with solution pH deviated from the isoelectric point of nanomaterials due to electrostatic repulsion. Moreover, tubular structures of TiO2 NTs with higher length-diameter ratio seem to aggregate more easily than dose sphere-like TiO2 NPs. This might be due to their spherical structure enhancing steric repulsion. Notably, the adsorption of HA led to disagglomeration and significant stability of TiO2 NPs and TiO2 NTs due to steric hindrance under varying solution pH. In addition, adsorption time, concentration and sources of HA also influenced suspension/sedimentation behavior of TiO2 NPs and TiO2 NTs, and aromatic-rich HAE stabilized TiO2 NMs suspension more aggressively than aliphatic-rich HAS.

Genotypic diversity of Salmonella ser. Abortusequi isolates from Argentina.

Salmonella enterica subsp. enterica serovar Abortusequi (S. Abortusequi) is a serotype restricted to equines, which produces abortion outbreaks. Nowadays the disease is being reported in different countries including Argentina thus generating an important impact in the equine industry. Molecular characterization of the 95 kb virulence plasmid and the spvC gene of S. Abortusequi demonstrated their importance in the pathogenicity of the serotype. In the last decades, high clonality of S. Abortusequi was identified in Japan, Mongolia and Croatia. The aim of this work was to characterize S. Abortusequi isolates obtained in Argentina between 2011 and 2016 by virulence-gene profiling and pulsed-field gel electrophoresis. Case report. S. Abortusequi isolates were studied by virulence-gene profiling and pulsed-field gel electrophoresis. Four virulence profiles and nine pulsed-field gel electrophoresis pulsotypes were identified among the 27 isolates included in the study. Different strains were found in the same outbreak and/or farm suggesting the presence of different sources of infection or mutation of isolates. The number of related and nonrelated strains. More isolates may be necessary for a more intensive study. Most strains presented the same virulence profile, being positive for all the studied genes except gipA and sopE1, which are involved in intestinal virulence. Only few isolates showed different results in the same outbreak or farm. Unlike other studies, our results demonstrate a considerable diversity of S. Abortusequi pulsed-field gel electrophoresis pulsotypes, which suggests that different sources of infection may be involved within the same outbreak.

Asteroid precision landing via Probabilistic Multiple-Horizon Multiple-Model Predictive Control

This paper seeks to provide a probabilistic control framework, named Probabilistic Multiple-Horizon Multiple-Model Predictive Control, for the soft and precise landing on an asteroid. The modified version of the Predictive Path Planning method is also introduced to generate a safe and smooth reference trajectory for landing. The Probabilistic Multiple-Horizon Multiple-Model Predictive Control is carried out in two phases; the offline phase to calculate the difference between models, and the online phase to use a probabilistic approach to track the reference trajectory. The difference of the dynamical models is utilized in the online control method to compensate the accuracy of the approximate models in the Multiple-Horizon Multiple-Model Predictive Control method. Furthermore, the presented control framework has the model-updating characteristic that helps to modify the prediction according to past information. The numerical simulation results demonstrate the effectiveness of the proposed guidance and control approach in the reduction of the fuel consumption as well as the landing error in the presence of different sources of uncertainties and disturbances.